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Scientific Reports
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July 11, 2024
Multiparametric MRI-based radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer
Rania M Mohamed, Bikash Panthi, Beatriz E Adrada, et al.
Frontiers in Oncology
|
November 9, 2023
Longitudinal dynamic contrast-enhanced MRI radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer
Bikash Panthi, Rania M Mohamed, Beatriz E Adrada, et al.
Journal of Magnetic Resonance Imaging : JMRI
|
May 2, 2022
Quantitative Apparent Diffusion Coefficients From Peritumoral Regions as Early Predictors of Response to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer
Benjamin C Musall, Beatriz E Adrada, Rosalind P Candelaria, et al.
Cancers
|
February 25, 2023
Assessment of Response to Neoadjuvant Systemic Treatment in Triple-Negative Breast Cancer Using Functional Tumor Volumes from Longitudinal Dynamic Contrast-Enhanced MRI
Bikash Panthi, Beatriz E Adrada, Rosalind P Candelaria, et al.
Journal of Magnetic Resonance Imaging : JMRI
|
January 31, 2024
Diffusion Tensor Imaging for Characterizing Changes in Triple-Negative Breast Cancer During Neoadjuvant Systemic Therapy
Benjamin C Musall, David E Rauch, Rania M M Mohamed, et al.
Journal of Magnetic Resonance Imaging : JMRI
|
February 15, 2021
Functional Tumor Volume by Fast Dynamic Contrast-Enhanced MRI for Predicting Neoadjuvant Systemic Therapy Response in Triple-Negative Breast Cancer
Benjamin C Musall, Abeer H Abdelhafez, Beatriz E Adrada, et al.
Breast Cancer Research and Treatment
|
September 13, 2020
Tumor necrosis by pretreatment breast MRI: association with neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC)
Abeer H Abdelhafez, Benjamin C Musall, Beatriz E Adrada, et al.
Cancers
|
October 14, 2023
Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast Cancer
Zhan Xu, David E Rauch, Rania M Mohamed, et al.
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of 6
Search research articles
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Showing results (51-60 of 58) with videos related to
Sort By:
Page
of 6
You have reached the last page of results.
This site can display upto 58 results.
Scientific Reports
|
July 11, 2024
Multiparametric MRI-based radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer
Rania M Mohamed, Bikash Panthi, Beatriz E Adrada, et al.
Frontiers in Oncology
|
November 9, 2023
Longitudinal dynamic contrast-enhanced MRI radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer
Bikash Panthi, Rania M Mohamed, Beatriz E Adrada, et al.
Journal of Magnetic Resonance Imaging : JMRI
|
May 2, 2022
Quantitative Apparent Diffusion Coefficients From Peritumoral Regions as Early Predictors of Response to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer
Benjamin C Musall, Beatriz E Adrada, Rosalind P Candelaria, et al.
Cancers
|
February 25, 2023
Assessment of Response to Neoadjuvant Systemic Treatment in Triple-Negative Breast Cancer Using Functional Tumor Volumes from Longitudinal Dynamic Contrast-Enhanced MRI
Bikash Panthi, Beatriz E Adrada, Rosalind P Candelaria, et al.
Journal of Magnetic Resonance Imaging : JMRI
|
January 31, 2024
Diffusion Tensor Imaging for Characterizing Changes in Triple-Negative Breast Cancer During Neoadjuvant Systemic Therapy
Benjamin C Musall, David E Rauch, Rania M M Mohamed, et al.
Journal of Magnetic Resonance Imaging : JMRI
|
February 15, 2021
Functional Tumor Volume by Fast Dynamic Contrast-Enhanced MRI for Predicting Neoadjuvant Systemic Therapy Response in Triple-Negative Breast Cancer
Benjamin C Musall, Abeer H Abdelhafez, Beatriz E Adrada, et al.
Breast Cancer Research and Treatment
|
September 13, 2020
Tumor necrosis by pretreatment breast MRI: association with neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC)
Abeer H Abdelhafez, Benjamin C Musall, Beatriz E Adrada, et al.
Cancers
|
October 14, 2023
Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast Cancer
Zhan Xu, David E Rauch, Rania M Mohamed, et al.
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of 6